The invention relates to a method and an apparatus for clustering process models and, in particular, to a method and an apparatus for ontology-based clustering of process models.
There exists a wide variety of processes, such as work processes in organizations or manufacturing processes for manufacturing or assembling devices. Processes can be described by using process models. Processes are modeled using different kinds of process modeling languages. An example for a process modeling language is the unified model language (UML). Processes can also be described by event-driven process chains (EPC). An EPC (Event-driven Process Chain) can be used, for example to define a business process workflow and is generated by EPC-tools. An event-driven process chain EPC is an ordered graph of events and functions. An EPC-graph provides various connectors that allow alternative and parallel execution of processes. Furthermore, there are specified logical operators, such as OR, AND or XOR.
A process model comprises a graph, wherein model elements are formed by nodes and relationships are normally represented by edges between said nodes. Process models can be stored in a data base.
For different applications, such as project planning in different fields, different kinds of process models are generated using different process modeling languages. The generated process models are stored in a database. Some of these process models are implemented in a real process or workflow. The implementation of a process model takes time and resources and can result in processes of different quality and efficiency.
A user faced with the task to analyze existing processes or to set up new processes, can evaluate process models stored in the database. The user can, for example define a process by generating a process model and look for other process models stored in the database which are similar to his process model or which fit to the required process. By finding a matching process model, the further implementation of the process model is facilitated and the user has the possibility to analyze whether the process model stored in the database and found during the search has led to an efficient implementation of the respective process. Accordingly, a user before implementing the defined process model can look at the implementation of an already implemented matching process model and decide whether the results of the already implemented process model are sufficient for the respective purposes of the new process model.
A manual search for matching process models is very time-consuming since in a conventional database a plurality of process models in different process model languages are stored. In a database, many thousands of different process models can be stored.
Accordingly, it is an object of the present invention to provide a method and an apparatus for finding automatically matching process models.